Optimizing lipid control in Taiwanese diabetic patients: A collaborative consensus by the Diabetes Association of the Republic of China (Taiwan) and the Taiwanese Association of Diabetes Educators.

We present an in-depth analysis of dyslipidemia management strategies for patients with diabetes mellitus in Taiwan. It critically examines the disparity between established guideline recommendations and actual clinical practices, particularly in the context of evolving policies affecting statin prescriptions. The focus is on synthesizing the most recent findings concerning lipid management in patients with diabetes mellitus, with a special emphasis on establishing consensus regarding low-density lipoprotein cholesterol treatment targets. The article culminates in providing comprehensive, evidence-based recommendations tailored to the unique needs of those living with diabetes mellitus in Taiwan. It underscores the criticality of personalized care approaches, which incorporate multifaceted factors, and the integration of novel therapeutic options to enhance cardiovascular health outcomes.

Disparities in prevalence and treatment of diabetes, cardiovascular and chronic kidney diseases - Recommendations from the taskforce of the guideline workshop.

There is a mounting clinical, psychosocial, and socioeconomic burden worldwide as the prevalence of diabetes, cardiovascular disease (CVD), and chronic kidney disease (CKD) continues to rise. Despite the introduction of therapeutic interventions with demonstrated efficacy to prevent the development or progression of these common chronic diseases, many individuals have limited access to these innovations due to their race/ethnicity, and/or socioeconomic status (SES). However, practical guidance to providers and healthcare systems for addressing these disparities is often lacking. In this article, we review the prevalence and impact of healthcare disparities derived from the above-mentioned chronic conditions and present broad-based recommendations for improving access to quality care and health outcomes within the most vulnerable populations.

Determinants of early chronic kidney disease in patients with recently diagnosed type 2 diabetes mellitus: a retrospective study from the Taiwan Diabetes Registry.

BACKGROUND: We tried to identify the risk factor associate with early chronic kidney disease (CKD) in recently diagnosed type 2 diabetes mellitus patients by utilizing real-world data from Taiwan Diabetes Registry. MATERIALS AND METHODS: Patients with type 2 diabetes mellitus recently diagnosed within 1 year. We divided the study participants into control group and early CKD group. Early CKD was defined as either CKD stage G1 with albuminuria, CKD stage G2 with albuminuria, or CKD stage G3a regardless of albuminuria (Urine-albumin to creatinine ratio (UACR) ≥ 3 mg/mmol). Control group was defined as CKD G1 or CKD G2 without albuminuria. Logistic regression analyses were used to compare differences in clinical characteristics between the subgroups. Linear regression models were employed to examine the factors predicting estimated glomerular filtration rate (eGFR) and UACR. RESULTS: Total 2217 patients with recently diagnosed type 2 diabetes mellitus were included. 1545 patients were assigned to control group and 618 patients were assigned to the early CKD group. Age (odds ratio (OR) 1.215, 95% confidence interval [CI] 1.122-1.316), systolic blood pressure (OR 1.203, 95% CI 1.117-1.296), glycated hemoglobin (OR 1.074, 95% CI 1.023-1.129) and triglyceride (OR 2.18, 95% CI 1.485-3.199) were found to be significant risk factors. Further, presence of bidirectional association between UACR and eGFR was found. CONCLUSIONS: We reported factors associated with early CKD in recently diagnosed type 2 diabetes mellitus patients. Variables that associated with eGFR and UACR were identified respectively, included a mutual influence between UACR and eGFR.

Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization.

BACKGROUND: Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (CHD; PRSCHD) for 5 genetic ancestry groups. METHODS: We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSPT) and ancestry-based continuous shrinkage priors (PRSCSx) applied to summary statistics from the largest multi-ancestry genome-wide association study meta-analysis for CHD to date, including 1.1 million participants from 5 major genetic ancestry groups. Following training and optimization in the Million Veteran Program, we evaluated the best-performing PRSCHD in 176,988 individuals across 9 diverse cohorts. RESULTS: Multi-ancestry PRSPT and PRSCSx outperformed ancestry-specific PRSPT and PRSCSx across a range of tuning values. Two best-performing multi-ancestry PRSCHD (ie, PRSPTmult and PRSCSxmult) and 1 ancestry-specific (PRSCSxEUR) were taken forward for validation. PRSPTmult demonstrated the strongest association with CHD in individuals of South Asian ancestry and European ancestry (odds ratio per 1 SD [95% CI, 2.75 [2.41-3.14], 1.65 [1.59-1.72]), followed by East Asian ancestry (1.56 [1.50-1.61]), Hispanic/Latino ancestry (1.38 [1.24-1.54]), and African ancestry (1.16 [1.11-1.21]). PRSCSxmult showed the strongest associations in South Asian ancestry (2.67 [2.38-3.00]) and European ancestry (1.65 [1.59-1.71]), lower in East Asian ancestry (1.59 [1.54-1.64]), Hispanic/Latino ancestry (1.51 [1.35-1.69]), and the lowest in African ancestry (1.20 [1.15-1.26]). CONCLUSIONS: The use of summary statistics from a large multi-ancestry genome-wide meta-analysis improved the performance of PRSCHD in most ancestry groups compared with single-ancestry methods. Despite the use of one of the largest and most diverse sets of training and validation cohorts to date, improvement of predictive performance was limited in African ancestry. This highlights the need for larger genome-wide association study datasets of underrepresented populations to enhance the performance of PRSCHD.

Precision subclassification of type 2 diabetes: a systematic review.

BACKGROUND: Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. METHODS: We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. RESULTS: Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. CONCLUSION: Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

In people with type 2 diabetes there may be differences in the way people present, including for example, their symptoms, body weight or how much insulin they make. We looked at recent publications describing research in this area to see whether it is possible to separate people with type 2 diabetes into different subgroups and, if so, whether these groupings were useful for patients. We found that it is possible to group people with type 2 diabetes into different subgroups and being in one subgroup can be more strongly linked to the likelihood of developing complications over others. This might mean that in the future we can treat people in different subgroups differently in ways that improves their treatment and their health but it requires further study.

Prevalence and prognosis of genetically proven familial hypercholesterolemia in subjects with coronary artery disease and reduced ejection fraction.

Few studies have genetically screened variants related to familial hypercholesterolemia (FH) and investigated their survival impact in patients with coronary artery disease (CAD) and reduced left ventricular ejection fraction (EF). Patients with CAD and reduced EF (< 40%) were enrolled. Their genomic DNAs were sequenced for FH-related genes. All-cause and cardiovascular mortality data served as the major outcome. A total of 256 subjects were analyzed and 12 subjects (4.7%) carried FH-related genetic variants. After a median follow-up period of 44 months, 119 of the study subjects died. Cox survival analysis showed that carrying the FH genetic variant did not have a significant impact on the survival of CAD with reduced EF. However, higher estimated glomerular filtration rate (eGFR), better EF and beta blocker use were protective for a lower all-cause mortality. Further larger studies are needed to evaluate the impact of carrying the FH-related genetic variant on survival of CAD with reduced EF.

Data from network meta-analyses can inform clinical practice guidelines and decision-making in diabetes management: perspectives of the taskforce of the guideline workshop.

In recent years, several novel agents have become available to treat individuals with type 2 diabetes (T2D), such as sodium-glucose cotransporter-2 inhibitors (SGLT-2i), tirzepatide, which is a dual glucose-dependent insulinotropic polypeptide receptor agonist (GIP RA)/glucagon-like peptide-1 receptor agonist (GLP-1 RA), and finerenone, a non-steroidal mineralocorticoid receptor antagonist (MRA) that confers significant renal and cardiovascular benefits in individuals with (CKD). New medications have the potential to improve the lives of individuals with diabetes. However, clinicians are challenged to understand the benefits and potential risks associated with these new and emerging treatment options. In this article, we discuss how use of network meta-analyses (NMA) can fill this need.

A Higher Estimated Glomerular Filtration Rate Is Associated with Better Survival in Subjects with Coronary Artery Disease and Heart Failure with a Mildly Reduced Ejection Fraction.

Subjects with coronary artery disease (CAD) have myocardial ischemia and associated abnormal left ventricular ejection fraction (EF). Heart failure with mildly reduced EF (41-49%) (HFmrEF) is a new subgroup of EF for heart failure. Although prognostic factors for CAD and HF with reduced EF are well known, fewer studies have been conducted on factors related to the survival of CAD and HFmrEF. We recruited study subjects with significant CAD and HFmrEF from our cardiac catheterization data bank. Data were recorded from traceable chart records from our hospital. All-cause and cardiovascular mortality were recorded until December 2019 and served as a follow-up outcome. A total of 348 subjects with CAD and HFmrEF were analyzed. The median duration of follow-up was 37 months. Seventy-eight subjects died during the follow-up period and 30 of them were due to cardiovascular causes. In univariate analyses, those who died were of older ages, and with a lower estimated glomerular filtration rate (eGFR) (47 ± 30 versus 71 ± 30 mL/minute/1.73 m2, P < 0.001), and lower usage of percutaneous coronary intervention (PCI) and beta blockers. In the Cox survival regression analysis, a higher eGFR (hazard ratio 0.980, P < 0.001) was protective, while older age and a higher serum total cholesterol (hazard ratio 1.006, P = 0.048) were related to all-cause mortality for CAD with HFmrEF. Furthermore, a higher eGFR was also associated with less cardiovascular mortality. In conclusion, for subjects with CAD and HFmrEF, a higher eGFR was protective and associated with a lower all-cause and cardiovascular mortality.

Plasma aryl hydrocarbon receptor associated with epicardial adipose tissue in men: a cross-sectional study.

BACKGROUND: Epicardial adipose tissue (EAT) is a type of ectopic fat with endocrine and paracrine functions. Aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that responds to environmental stimuli. AhR expression is associated with obesity. In this cross-sectional study, we aimed to determine the relationship between circulating AhR concentrations and EAT. METHODS: A total of 30 men with obesity and 23 age-matched men as healthy controls were enrolled. Plasma AhR concentrations were determined at fasting. The EAT thickness was measured on the free wall of the right ventricle from the basal short-axis plane by magnetic resonance imaging. RESULTS: The participants with obesity had a higher plasma AhR level than the controls (81.0 ± 24.5 vs. 65.1 ± 16.4 pg/mL, P = 0.010). The plasma AhR level was positively correlated with EAT thickness (correlation coefficient = 0.380, P = 0.005). After adjusting for fasting glucose levels, plasma AhR levels were still significantly associated with EAT thickness (95% CI 0.458‒5.357, P = 0.021) but not with body mass index (P = 0.168). CONCLUSION: Plasma AhR concentrations were positively correlated with EAT thickness on the free wall of the right ventricle in men. Further investigations are needed to evaluate the causal effects and underlying mechanisms between AhR and EAT.

A Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization.

Background: Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (PRSCHD) for 5 genetic ancestry groups. Methods: We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSP+T) and continuous shrinkage priors (PRSCSx) applied on summary statistics from the largest multi-ancestry genome-wide meta-analysis for CHD to date, including 1.1 million participants from 5 continental populations. Following training and optimization of PRSCHD in the Million Veteran Program, we evaluated predictive performance of the best performing PRSCHD in 176,988 individuals across 9 cohorts of diverse genetic ancestry. Results: Multi-ancestry PRSP+T outperformed ancestry specific PRSP+T across a range of tuning values. In training stage, for all ancestry groups, PRSCSx performed better than PRSP+T and multi-ancestry PRS outperformed ancestry-specific PRS. In independent validation cohorts, the selected multi-ancestry PRSP+T demonstrated the strongest association with CHD in individuals of South Asian (SAS) and European (EUR) ancestry (OR per 1SD[95% CI]; 2.75[2.41-3.14], 1.65[1.59-1.72]), followed by East Asian (EAS) (1.56[1.50-1.61]), Hispanic/Latino (HIS) (1.38[1.24-1.54]), and weakest in African (AFR) ancestry (1.16[1.11-1.21]). The selected multi-ancestry PRSCSx showed stronger associacion with CHD in comparison within each ancestry group where the association was strongest in SAS (2.67[2.38-3.00]) and EUR (1.65[1.59-1.71]), progressively decreasing in EAS (1.59[1.54-1.64]), HIS (1.51[1.35-1.69]), and lowest in AFR (1.20[1.15-1.26]). Conclusions: Utilizing diverse summary statistics from a large multi-ancestry genome-wide meta-analysis led to improved performance of PRSCHD in most ancestry groups compared to single-ancestry methods. Improvement of predictive performance was limited, specifically in AFR and HIS, despite use of one of the largest and most diverse set of training and validation cohorts to date. This highlights the need for larger GWAS datasets of AFR and HIS individuals to enhance performance of PRSCHD.

Empagliflozin is associated with lower cardiovascular risk compared with dipeptidyl peptidase-4 inhibitors in adults with and without cardiovascular disease: EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) study results from Europe and Asia.

BACKGROUND: Studies that have reported lower risk for cardiovascular outcomes in users of Sodium-Glucose Cotransporter-2 Inhibitors (SGLT-2i) are limited by residual cofounding and lack of information on prior cardiovascular disease (CVD). This study compared risk of cardiovascular events in patients within routine care settings in Europe and Asia with type 2 diabetes (T2D) initiating empagliflozin compared to dipeptidyl peptidase-4 inhibitors (DPP-4i) stratified by pre-existing CVD and history of heart failure (HF). METHODS AND RESULTS: Adults initiating empagliflozin and DPP-4i in 2014-2018/19 from 11 countries in Europe and Asia were compared using propensity score matching and Cox proportional hazards regression to assess differences in rates of primary outcomes: hospitalisation for heart failure (HHF), myocardial infarction (MI), stroke; and secondary outcomes: cardiovascular mortality (CVM), coronary revascularisation procedure, composite outcome including HHF or CVM, and 3-point major adverse cardiovascular events (MACE: MI, stroke and CVM). Country-specific results were meta-analysed and pooled hazard ratios (HR) with 95% confidence intervals (CI) from random-effects models are presented. In total, 85,244 empagliflozin/DPP4i PS-matched patient pairs were included with overall mean follow-up of 0.7 years. Among those with pre-existing CVD, lower risk was observed for HHF (HR 0.74; 95% CI 0.64-0.86), CVM (HR 0.55; 95% CI 0.38-0.80), HHF or CVM (HR 0.57; 95% CI 0.48-0.67) and stroke (HR 0.79; 95% CI 0.67-0.94) in patients initiating empagliflozin vs DPP-4i. Similar patterns were observed among patients without pre-existing CVD and those with and without pre-existing HF. CONCLUSION: These results from diverse patient populations in routine care settings across Europe and Asia demonstrate that initiation of empagliflozin compared to DPP-4i results in favourable cardioprotective effects regardless of pre-existing CVD or HF status.

A risk stratification model modified from the U.S. guideline could be applied in an Asian population with or without ASCVD.

AIM: This study aimed to evaluate the performance of a modified US (MUS) model for risk prediction of cardiovascular (CV) events in Asian patients and compare it to European and Japanese models. MATERIAL AND METHODS: The MUS model, based on the US ACC/AHA 2018 lipid treatment guideline, was employed to stratify patients under primary or secondary prevention. Two multi-center prospective observational registry cohorts, T-SPARCLE and T-PPARCLE, were used to validate the scoring system, and the primary outcome was the time to first occurrence/recurrence of major adverse cardiac events (MACEs). The MUS model's performance was compared to other models from Europe and Japan. RESULTS: A total of 10,733 patients with the mean age of 64.2 (SD: 11.9) and 36.5% female were followed up for a median of 5.4 years. The MUS model was validated, with an AUC score of 0.73 (95% CI 0.68-0.78). The European and Japanese models had AUC scores ranging from 0.6 to 0.7. The MUS model categorized patients into four distinct CV risk groups, with hazard ratios (HRs) as follows: very high-vs. high-risk group (HR=1.91, 95% CI 1.53-2.39), high-vs. moderate-risk group (HR=2.08, 95% CI 1.60-2.69), and moderate-vs. low-risk group (HR=3.14, 95% CI 1.63-6.03). After adjusting for the MUS model, a history of ASCVD was not a significant predictor of adverse cardiovascular outcomes within each risk group. CONCLUSION: The MUS model is an effective tool for risk stratification in Asian patients with and without ASCVD, accurately predicting MACEs and performing comparably or better than other established risk models. Our findings suggest that patient management should focus on background risk factors instead of solely on primary or secondary prevention.

Device-supported automated basal insulin titration in adults with type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials.

Background: Technological advances make it possible to use device-supported, automated algorithms to aid basal insulin (BI) dosing titration in patients with type 2 diabetes. Methods: A systematic review and meta-analysis of randomized controlled trials were performed to evaluate the efficacy, safety, and quality of life of automated BI titration versus conventional care. The literature in Medline, Embase, Web of Science, and the Cochrane databases from January 2000 to February 2022 were searched to identify relevant studies. Risk ratios (RRs), mean differences (MDs), and their 95% confidence intervals (CIs) were calculated using random-effect meta-analyses. Certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. Findings: Six of the 7 eligible studies (889 patients) were included in meta-analyses. Low- to moderate-quality evidence suggests that patients who use automated BI titration versus conventional care may have a higher probability of reaching a target of HbA1c <7.0% (RR, 1.82 [95% CI, 1.16-2.86]); and a lower level of HbA1c (MD, -0.25% [95% CI, -0.43 to -0.06%]). No statistically significant differences were detected between the two groups in fasting glucose results, incidences of hypoglycemia, severe or nocturnal hypoglycemia, and quality of life, with low to very low certainty for all the evidence. Interpretation: Automated BI titration is associated with small benefits in reducing HbA1c without increasing the risk of hypoglycemia. Future studies should explore patient attitudes and the cost-effectiveness of this approach. Funding: Sponsored by the Chinese Geriatric Endocrine Society.

Accuracy of Point-of-Care Blood Glucometers in Neonates and Critically Ill Adults.

PURPOSE: Inpatient glycemic management has become a common issue because of the increasing number of hospitalized patients with hyperglycemia. Point-of-care devices can enable timely inpatient glucose monitoring, which may lead to better outcomes. The accuracy of point-of-care testing in various clinical scenarios has been questioned, particularly in neonates and critically ill patients. This study aimed to evaluate the accuracy of the CONTOUR PLUS and CONTOUR PLUS ONE glucometers (new wireless systems that link to a smart mobile device) when used as point-of-care devices for blood glucose monitoring in neonates and critically ill adults in inpatient settings. METHODS: This cross-sectional study was conducted at a medical center in central Taiwan and enrolled patients admitted to the neonatal intensive care unit, sick child room, or respiratory intensive care unit between November 2020 and April 2021. Neonates with suspected infection or abnormal blood coagulation and adults who had abnormal blood coagulation, were pregnant, had received organ transplants, or had undergone massive blood transfusions were excluded. The accuracy of the glucometers was determined based on the following criteria of the International Organization for Standardization (ISO) standard: 15197:2013. FINDINGS: Overall, 114 neonates (mean age, 4.2 days [range, 0-28 days]; 65 boys [57.0%]) and 106 hospitalized critically ill adults (mean age, 68.2 years [range, 27-94 years]; 72 men [67.9%]) were enrolled in this study. The glucose values obtained with each glucometer had good precision, and all findings met the reference criteria of the within-lot results. All measurements of the neonates' venous blood by each glucometer met the accuracy criteria specified by ISO standard 15197:2013. Furthermore, 98.1% and 97.2% of the arterial blood glucose measurements for critically ill adults obtained with CONTOUR PLUS and CONTOUR PLUS ONE met the accuracy criteria, respectively. IMPLICATIONS: Both glucose management systems met the accuracy criteria for venous blood from neonates and arterial blood from critically ill adults. Thus, the use of these 2 point-of-care devices in inpatient settings, including for neonates and critically ill adults, can be recommended to minimize limitations associated with the clinical application of point-of-care testing in glucose management. The wireless connection may play a role in the subsequent development of institution-wide virtual glycemic management under the supervision of a team of endocrinologists.

Systematic review of precision subclassification of type 2 diabetes.

Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.

Association of Major Adverse Cardiac Events and Beta-Blockers in Patients with and without Atherosclerotic Cardiovascular Disease: Long-Term Follow-Up Results of the T-SPARCLE and T-PPARCLE Registry in Taiwan.

Beta-blockers are widely used, but the benefit is now challenged in patients at risk of atherosclerotic cardiovascular disease (ASCVD) in the present coronary reperfusion era. We aimed to identify the risk factors of a major adverse cardiac event (MACE) and the long-term effect of beta-blockers in two large cohorts in Taiwan. Two prospective observational cohorts, including patients with known atherosclerosis cardiovascular disease (T-SPARCLE) and patients with at least one risk factor of ASCVD but without clinically evident ASCVD (T-PPARCLE), were conducted in Taiwan. The primary endpoint is the time of first occurrence of a MACE (cardiovascular death, nonfatal stroke, nonfatal myocardial infarction, and cardiac arrest with resuscitation). Between December 2009 and November 2014, with a median 2.4 years follow-up, 11,747 eligible patients (6921 and 4826 in T-SPARCLE and T-PPARCLE, respectively) were enrolled. Among them, 273 patients (2.3%) met the primary endpoint. With multivariate Cox PH model analysis, usage of beta-blocker was lower in patients with MACE (42.9% vs. 52.4%, p < 0.01). In patients with ASCVD, beta-blocker usage was associated with lower MACEs (hazard ratio 0.72; p < 0.001), but not in patients without ASCVD. The event-free survival of beta-blocker users remained higher during the follow-up period (p < 0.005) of ASCVD patients. In conclusion, in ASCVD patients, reduced MACE was associated with beta-blocker usage, and the effect was maintained during a six-year follow-up. Prescribing beta-blockers as secondary prevention is reasonable in the Taiwanese population.

Prediction of the risk of developing end-stage renal diseases in newly diagnosed type 2 diabetes mellitus using artificial intelligence algorithms.

OBJECTIVES: Type 2 diabetes mellitus (T2DM) imposes a great burden on healthcare systems, and these patients experience higher long-term risks for developing end-stage renal disease (ESRD). Managing diabetic nephropathy becomes more challenging when kidney function starts declining. Therefore, developing predictive models for the risk of developing ESRD in newly diagnosed T2DM patients may be helpful in clinical settings. METHODS: We established machine learning models constructed from a subset of clinical features collected from 53,477 newly diagnosed T2DM patients from January 2008 to December 2018 and then selected the best model. The cohort was divided, with 70% and 30% of patients randomly assigned to the training and testing sets, respectively. RESULTS: The discriminative ability of our machine learning models, including logistic regression, extra tree classifier, random forest, gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and light gradient boosting machine were evaluated across the cohort. XGBoost yielded the highest area under the receiver operating characteristic curve (AUC) of 0.953, followed by extra tree and GBDT, with AUC values of 0.952 and 0.938 on the testing dataset. The SHapley Additive explanation summary plot in the XGBoost model illustrated that the top five important features included baseline serum creatinine, mean serum creatine within 1 year before the diagnosis of T2DM, high-sensitivity C-reactive protein, spot urine protein-to-creatinine ratio and female gender. CONCLUSIONS: Because our machine learning prediction models were based on routinely collected clinical features, they can be used as risk assessment tools for developing ESRD. By identifying high-risk patients, intervention strategies may be provided at an early stage.

Unhealthy lifestyle associated with increased risk of macro- and micro-vascular comorbidities in patients with long-duration type 2 diabetes: results from the Taiwan Diabetes Registry.

BACKGROUND: Unhealthy lifestyle has been associated with obesity and type 2 diabetes. Whereas its association with vascular complications in patients with long-duration of type 2 diabetes is still uncertain. METHODS: A total of 1188 patients with long-duration of type 2 diabetes from the Taiwan Diabetes Registry (TDR) data were analyzed. We stratified the severity of unhealthy lifestyle via scoring three factors (sleep duration <7 or >9 h, sit duration ≥ 8h, and meal numbers ≥ with night snack) and analyzed their associations with the development of vascular complications using logistic regression analysis. Besides, we also included 3285 patients with newly diagnosed type 2 diabetes as the comparison. RESULTS: Increased numbers of factors that stand for unhealthy lifestyle were significantly associated with the development of cardiovascular disease, peripheral arterial occlusion disease (PAOD) and nephropathy in patients with long-duration of type 2 diabetes. After adjusting multiple covariables, having ≥ 2 factors of unhealthy lifestyle remained significant associations with cardiovascular disease and PAOD, with an odds ratio (OR) of 2.09 (95% confidence interval [CI] 1.18-3.69) and 2.68 (95% CI 1.21-5.90), respectively. Among individual factor for unhealthy lifestyle behaviors, we revealed that eating ≥ 4 meals per day with night snack increased the risk of cardiovascular disease and nephropathy after multivariable adjustment (OR of 2.60, 95% CI 1.28-5.30; OR of 2.54, 95% CI 1.52-4.26, respectively). Whereas sit duration for ≥ 8 h per day increased the risk of PAOD (OR of 4.32, 95% CI 2.38-7.84). CONCLUSION: Unhealthy lifestyle is associated with increased prevalence of macro- and micro-vascular comorbidities in Taiwanese patients with long-duration type 2 diabetes.

Brain-derived neurotrophic factor associated with kidney function.

BACKGROUND: We examined the relationship between brain-derived neurotrophic factor (BDNF) and chronic kidney disease (CKD). METHODS: First, a cross-sectional study was conducted in 480 participants without known diabetes. An oral glucose tolerance test (OGTT) was administered after overnight fasting, and blood samples were collected at 0, 30, and 120 min. Second, a total of 3003 participants were enrolled for the case-control genetic analysis. After assigning them to a case or a control group based on age and CKD status, we investigated the association between BDNF gene variants and susceptibility to CKD. RESULTS: A higher fasting serum BDNF quartile was significantly associated with a lower prevalence of CKD (P value for trend < 0.001). Based on the receiver operating characteristic analysis, the fasting BDNF level had a larger area under the curve for differentiating CKD (0.645, 95% CI 0.583‒0.707) than the BDNF levels at both 30 min (0.547, 95% CI 0.481‒0.612) and 120 min (0.598, 95% CI 0.536‒0.661). A significantly lower CKD prevalence (odds ratio = 0.30, 95% CI 0.12‒0.71) was observed in the highest quartile of fasting BDNF level than that in the lowest quartile, whereas no interquartile differences were observed for BDNF levels determined at 30 or 120 min during the OGTT. Furthermore, BDNF-associated variants, including rs12098908, rs12577517, and rs72891405, were significantly associated with CKD. CONCLUSIONS: The BDNF level at fasting, but not at 30 and 120 min after glucose intake, was an independent indicator of CKD. In addition, significant associations were observed between three BDNF gene variants and CKD.